saving model to ./chkpt/model_epoch70.pt
do evaluation ......

do scoring ......

epoch = 70 cosine eer% = 99.95%

Drawing tsne of latent space ......
select speakers with utts large than 250
n_samples=6403, n_dim=(512,), n_labels=22
Computing t-SNE embedding epoch
Traceback (most recent call last):
File "train.py", line 294, in
tsne.main(path0,epoch)
File "/MG-master/tsne.py", line 70, in main
result = tsne.fit_transform(data)
File "/pytorch/lib64/python3.6/site-packages/sklearn/manifold/_t_sne.py", line 932, in fit_transform
embedding = self._fit(X)
File "/pytorch/lib64/python3.6/site-packages/sklearn/manifold/_t_sne.py", line 704, in _fit
dtype=[np.float32, np.float64])
File "/pytorch/lib64/python3.6/site-packages/sklearn/base.py", line 421, in _validate_data
X = check_array(X, **check_params)
File "/pytorch/lib64/python3.6/site-packages/sklearn/utils/validation.py", line 63, in inner_f
return f(*args, **kwargs)
File "/pytorch/lib64/python3.6/site-packages/sklearn/utils/validation.py", line 664, in check_array
allow_nan=force_all_finite == 'allow-nan')
File "/pytorch/lib64/python3.6/site-packages/sklearn/utils/validation.py", line 106, in _assert_all_finite
msg_dtype if msg_dtype is not None else X.dtype)
ValueError: Input contains NaN, infinity or a value too large for dtype('float32').

input data have NaN? why? can you help to fix it?